36 tech influencers on X (Twitter) to follow or partner with in 2026

I recently created a list of 17 tech YouTubers to follow or partner with in 2026. This time, I wanted to do the same for X (formerly Twitter).

Some of the most useful technical discussions I come across on X are from people building the tools developers use.

Simon Willison regularly shares his LLM experiments, Mitchell Hashimoto discusses building developer tools such as Ghostty, and Chip Huyen writes about the challenges of building production AI systems.

I put together this list for two groups: developers looking for people they can learn from, and DevTools companies looking for creators who reach the software engineers they want to acquire.

To make the list useful, I used the X API to collect publicly available data for 50 accounts on November 4, 2026.

I shortlisted 36 tech influencers covering AI, coding, cloud infrastructure, cybersecurity, data engineering, and Web3.

Along with their profiles, I've included follower counts and average post impressions so you can see how their content performs.

How I selected these tech influencers on X

I started with 50 X accounts and shortlisted 36 based on the following criteria:

• Technical relevance: I selected software engineers, AI researchers, DevTools founders, and technical educators who regularly share useful content for developers.
• Audience size: I used the X API to collect follower counts as of November 4, 2026.
• Post performance: I analyzed up to 10 posts per account and calculated average impressions, likes, replies, and reposts.
• Content activity: I excluded replies and reposts from the analysis but included quote posts. I also checked publishing frequency and recent activity.
• Data quality: I removed accounts with inactive or unverifiable profiles, insufficient usable data, or content that wasn't relevant to developers.

A note on the data: All metrics were collected using the X API on November 4, 2026. Some accounts had fewer than 10 usable posts, and the sampling periods varied. Average impressions represent the collected posts and shouldn't be treated as guaranteed reach for an influencer campaign.

All 36 tech influencers on X at a glance: followers, average impressions, and topics

Tech influencer	Main topic	Followers	Avg. post impressions
Vitalik Buterin	Ethereum, protocols	7,930,893	460,465
Andrej Karpathy	AI research	4,425,681	4,731,848
Andrew Ng	AI education	1,959,301	2,091,828
ZachXBT	Blockchain investigations	1,115,990	428,419
David Heinemeier Hansson	Ruby on Rails, software	946,382	57,606
Guillermo Rauch	Vercel, Next.js	917,053	37,466
François Chollet	Deep learning, reasoning	753,165	206,112
Sebastian Raschka	LLMs, machine learning	534,515	35,540
Addy Osmani	Web performance, tooling	485,149	656,660
Wes Bos	JavaScript, CSS	446,659	41,300
Theo Browne	Frontend, TypeScript	420,041	56,034
SwiftOnSecurity	Cybersecurity, sysadmin	416,759	11,001
ThePrimeagen	Programming, editors	390,326	48,602
Gergely Orosz	Engineering leadership	365,751	46,472
Jesse Pollak	Base, Web3 development	355,898	23,968
Sarah Drasner	Frontend, developer experience	306,135	18,830
Marcus Hutchins	Malware analysis	277,945	27,093
Troy Hunt	Web security, breaches	256,749	7,804
Simon Willison	LLM tooling, security	249,831	85,246
Mitchell Hashimoto	Infrastructure, CLI tools	239,636	141,815
Riley Goodside	Prompt engineering	238,306	67,031
Mikko Hyppönen	Cybersecurity threats	226,294	53,324
Shawn Wang (swyx)	AI engineering	210,335	27,602
Cassidy Williams	Coding, developer careers	184,600	11,112
samczsun	Smart-contract security	160,636	15,596
Chip Huyen	AI engineering, MLOps	157,282	68,927
Harrison Chase	AI agents, LangChain	138,295	23,383
Jessie Frazelle	Linux, containers	134,982	36,252
Philipp Schmid	AI APIs, agents	126,362	34,984
Corey Quinn	AWS, cloud costs	108,899	5,154
Nathan Lambert	Open models, reinforcement learning	108,429	20,013
Jerry Liu	LlamaIndex, RAG	87,519	21,071
Omar Sanseviero	AI models, education	74,693	25,893
Hamel Husain	LLM evaluations	64,833	22,499
Shreya Shankar	AI evaluation, data systems	59,638	19,553
Cindy Sridharan	Observability, reliability	56,650	13,278

Source: X API, November 4, 2026. Average impressions are calculated from up to 10 sampled posts per account. Sample periods vary, and quote posts are included.

Top AI influencers on X

1. Andrej Karpathy (@karpathy)

X: @karpathy

Andrej Karpathy is known for his work in deep learning, including his time at OpenAI and Tesla.

His educational content explains neural networks, language models, and AI systems through code. His Neural Networks: Zero to Hero course is particularly useful if you want to understand how these models work internally.

2. Andrew Ng (@AndrewYNg)

X: @AndrewYNg

Andrew Ng is associated with DeepLearning.AI and Coursera, where his work has helped developers learn machine learning.

He shares AI research, educational resources, and developments in the industry. I'd follow him for a broader understanding of machine learning and its applications.

3. François Chollet (@fchollet)

X: @fchollet

François Chollet created Keras, the deep learning API used by machine learning developers. His research focuses on intelligence, reasoning, and evaluating AI systems. He's also known for developing the ARC benchmark.

His account is useful for following discussions about the limitations of AI models and how we measure their capabilities.

4. Sebastian Raschka (@rasbt)

X: @rasbt

Sebastian Raschka writes about machine learning, deep learning, and LLM development. He's the author of Build a Large Language Model (From Scratch) and frequently shares technical explanations of research papers, model architectures, and implementation techniques.

5. Simon Willison (@simonw)

X: @simonw

Simon Willison creates open-source developer tools such as Datasette and LLM, his command-line utility for working with language models. He regularly shares experiments involving AI models, prompt injection, and developer tooling.

His blog is also an excellent resource if you're building applications with LLMs.

6. Riley Goodside (@goodside)

X: @goodside

Riley Goodside explores prompt engineering and how language models interpret instructions. His posts often demonstrate unexpected model behavior through practical examples, making his work useful for developers experimenting with prompts and AI application security.

7. Shawn Wang (swyx) (@swyx)

X: @swyx

Shawn Wang is associated with the AI Engineer community and writes about building software with AI. His posts cover AI engineering, developer tools, new frameworks, and projects being developed across the AI ecosystem.

8. Nathan Lambert (@natolambert)

X: @natolambert

Nathan Lambert works on open language models and AI research. He discusses model training, reinforcement learning, evaluation, and developments in open-source AI.

His work is useful if you're interested in the technical decisions behind developing language models.

9. Harrison Chase (@hwchase17)

X: @hwchase17

Harrison Chase is the co-founder of LangChain. He shares developments in AI agents, orchestration frameworks, and tools for building LLM applications.

Developers working with LangChain or agent-based applications will find his discussions particularly relevant.

10. Jerry Liu (@jerryjliu0)

X: @jerryjliu0

Jerry Liu founded LlamaIndex, which helps developers build LLM applications using external data. His posts cover retrieval-augmented generation, document processing, and connecting language models with data sources.

11. Philipp Schmid (@_philschmid)

X: @_philschmid

Philipp Schmid creates technical content about AI models, agents, and developer APIs. He shares implementation examples and tutorials that help developers understand how to build applications using modern AI tools.

12. Omar Sanseviero (@osanseviero)

X: @osanseviero

Omar Sanseviero works in machine learning and AI developer education. He has contributed to the Hugging Face ecosystem and shares research, educational resources, and developments in AI tooling.

Data engineering, ML, and LLM evaluation influencers

13. Chip Huyen (@chipro)

X: @chipro

Chip Huyen writes about designing and operating machine learning systems. She's the author of Designing Machine Learning Systems and AI Engineering.

Her work covers model evaluation, data pipelines, and the engineering challenges involved in running AI applications in production.

14. Hamel Husain (@HamelHusain)

X: @HamelHusain

Hamel Husain focuses on LLM evaluations and improving the quality of AI applications. He shares practical approaches to evaluating model outputs, testing AI systems, and identifying problems that appear after an application moves beyond the demo stage.

I also included him in my YouTube list because his educational work is useful across both platforms.

15. Shreya Shankar (@sh_reya)

X: @sh_reya

Shreya Shankar researches data systems and the reliability of AI applications. Her work explores data quality, LLM evaluation, and the engineering practices required to build dependable applications using language models.

Coding and developer-tools influencers on X

16. Addy Osmani (@addyosmani)

X: @addyosmani

Addy Osmani is known for his work on JavaScript, web performance, and developer tooling. He writes about frontend engineering, application performance, and AI-assisted development.

His posts often explore practical problems developers encounter when building and maintaining web applications.

17. David Heinemeier Hansson (@dhh)

X: @dhh

David Heinemeier Hansson created Ruby on Rails and co-founded 37signals. He discusses software architecture, programming frameworks, infrastructure, and engineering decisions.

His account also covers broader business and technology topics, so the audience extends beyond software developers.

18. Theo Browne (@theo)

X: @theo

Theo Browne, also known as t3.gg, creates content about JavaScript, TypeScript, React, and modern web development. He frequently discusses frontend frameworks, developer experience, and AI coding tools.

His content is useful for developers working in the JavaScript ecosystem.

19. ThePrimeagen (@ThePrimeagen)

X: @ThePrimeagen

ThePrimeagen creates programming content and discusses the tools developers use every day. His topics include programming languages, code editors, terminal workflows, and software performance.

He's particularly relevant if you're interested in developer productivity and engineering workflows.

20. Wes Bos (@wesbos)

X: @wesbos

Wes Bos teaches JavaScript, React, CSS, and modern web development. He's also known for JavaScript30 and the Syntax podcast.

He shares programming tips, browser features, and frontend development resources.

21. Gergely Orosz (@GergelyOrosz)

X: @GergelyOrosz

Gergely Orosz writes The Pragmatic Engineer, a publication covering software engineering careers and how technology companies operate.

His work explores engineering organizations, hiring, technical decisions, and changes affecting software developers.

22. Sarah Drasner (@sarah_edo)

X: @sarah_edo

Sarah Drasner is known for her work in frontend development, JavaScript, Vue, and developer education. She also writes and speaks about engineering leadership and developer experience.

23. Cassidy Williams (@cassidoo)

X: @cassidoo

Cassidy Williams shares programming resources, coding challenges, developer career advice, and personal projects. Her newsletter also includes coding problems and useful tools for software developers.

Cloud, DevOps, and infrastructure influencers on X

24. Guillermo Rauch (@rauchg)

X: @rauchg

Guillermo Rauch is the founder and CEO of Vercel. He discusses web development, Next.js, frontend infrastructure, and the technologies developers use to build and deploy applications.

25. Mitchell Hashimoto (@mitchellh)

X: @mitchellh

Mitchell Hashimoto co-founded HashiCorp and helped create Terraform, Vagrant, and Vault. He's also the creator of Ghostty, a terminal emulator.

He shares his experience building developer tools, making engineering decisions, and working on open-source software.

26. Jessie Frazelle (@jessfraz)

X: @jessfraz

Jessie Frazelle is known for her work on Linux, containers, infrastructure, and developer tooling. Her technical work and discussions are useful for engineers interested in systems programming and infrastructure.

27. Corey Quinn (@QuinnyPig)

X: @QuinnyPig

Corey Quinn discusses AWS, cloud infrastructure, and the costs associated with running applications in the cloud. He's associated with Last Week in AWS and frequently comments on AWS developments, pricing, and cloud operations.

28. Cindy Sridharan (@copyconstruct)

X: @copyconstruct

Cindy Sridharan writes about distributed systems, observability, and production reliability. Her technical work explains how engineers monitor, debug, and operate complex software systems.

Cybersecurity influencers on X

29. SwiftOnSecurity (@SwiftOnSecurity)

X: @SwiftOnSecurity

SwiftOnSecurity is a pseudonymous account known for discussing cybersecurity, system administration, and security operations. The account combines technical observations with humor, often highlighting the mistakes and challenges security teams encounter.

30. Marcus Hutchins (@MalwareTechBlog)

X: @MalwareTechBlog

Marcus Hutchins is a security researcher known for his work analyzing malware and helping stop the WannaCry ransomware outbreak.

His technical work covers malware analysis, reverse engineering, and cybersecurity research.

31. Mikko Hyppönen (@mikko)

X: @mikko

Mikko Hyppönen is a cybersecurity researcher who investigates malware, cybercrime, and digital security threats.

He shares information about security incidents and developments affecting organizations and internet users.

32. Troy Hunt (@troyhunt)

X: @troyhunt

Troy Hunt created Have I Been Pwned, a service that helps people check whether their information has appeared in known data breaches. He writes about web application security, authentication, data breaches, and privacy.

Crypto and Web3 influencers on X

33. Vitalik Buterin (@VitalikButerin)

X: @VitalikButerin

Vitalik Buterin is the co-founder of Ethereum. He writes about blockchain architecture, protocol development, cryptography, and technical decisions affecting Ethereum.

He's included because of his influence on blockchain development, rather than as a conventional influencer sponsorship prospect.

34. Jesse Pollak (@jessepollak)

X: @jessepollak

Jesse Pollak is associated with Base, the Ethereum layer-2 network developed by Coinbase. His posts cover blockchain development, the Base ecosystem, and applications being built on the network.

35. ZachXBT (@zachxbt)

X: @zachxbt

ZachXBT investigates cryptocurrency scams and suspicious blockchain activity. His research often uses publicly available blockchain data to trace transactions and uncover fraudulent activity.

36. samczsun (@samczsun)

X: @samczsun

samczsun is known for smart-contract security research and investigating vulnerabilities in blockchain applications. He is also associated with SEAL, an organization focused on protecting the cryptocurrency ecosystem.

His work is useful for developers interested in smart-contract security and blockchain infrastructure.

How to choose X influencers for a developer product

If I were marketing an LLM observability platform, I'd start with creators like Hamel Husain, Simon Willison, and Shreya Shankar. They regularly discuss LLM evaluations, model behavior, and problems developers encounter when building AI applications.

Their content is relevant to the engineers who might need an observability platform. However, I'd still evaluate their audience and recent activity before considering a partnership.

Here's how I'd approach it.

1. Find creators who talk about the problems your product solves

Start by identifying the developers you want to reach and the technologies they work with.

For example, if you're marketing a Kubernetes monitoring tool, I'd look for creators discussing cluster performance, deployment failures, and debugging production workloads.

If you're promoting an AI SDK, I'd shortlist engineers sharing code examples, integration tutorials, and experiences building LLM applications.

I'd also read the replies to see whether developers are asking questions about these problems.

2. Check their recent posts and engagement

I'd review at least 10 recent posts from each shortlisted creator, focusing on content related to the product category.

I'd record their average impressions, likes, replies, and reposts. I'd also check how frequently they publish and whether their technical posts consistently attract engagement.

For example, a creator with 50,000 followers whose Kubernetes tutorials regularly receive questions from platform engineers could be relevant to an infrastructure company.

I'd also ask for examples of previous technical collaborations and their performance, where available.

3. Choose a collaboration that demonstrates your product

Once I've identified suitable creators, I'd check whether they're open to partnerships and discuss what they could produce.

For an API product, I'd propose a technical walkthrough where the creator signs up, authenticates, makes an API request, and builds a small application.

For an observability platform, the creator could demonstrate how to identify a failing LLM request, inspect its traces, and debug the issue.

I'd provide product access, documentation, and technical support so the creator can test the integration before publishing.

4. Measure how many developers actually use your product

Before launching the campaign, I'd agree on what success looks like and set up tracking.

I'd use unique UTM links for each creator and measure website visits, documentation visits, signups, and product activation.

For an API company, that could mean tracking how many referred developers complete their first successful API request. For a database company, it could mean measuring how many developers run their first query.

This helps me understand which creator partnerships are bringing in developers who actually try the product and where to invest in future campaigns.

For more ideas on reaching software engineers, I've covered other options in our guide to developer marketing channels.

Acquire more software engineers through influencer marketing with Hackmamba

Finding tech influencers is only the first part of running a developer acquisition campaign. You need to identify creators whose audiences match the engineers you want to reach and give those developers a reason to try your product.

At Hackmamba, we help DevTools and developer-focused companies acquire software engineers through tech influencer marketing.

We research technical creators, identify suitable partnerships, manage outreach, and help produce content that demonstrates your product through tutorials, walkthroughs, and integrations.

We also support distribution and measure what happens after developers engage with the campaign, from signups to first API calls and product activation.

If you're planning an influencer marketing campaign to reach more software engineers, talk to our team.